Monday, February 24, 2014

Data Warehouse Design and Dimensional Modeling


Within organizations, information is typically categorized into two different areas. There are operational databases that are used for online transaction processing (OLTP), and there are data warehouses and data marts used for online analytically processing (OLAP). OLTP database users tend to be operational users who enter data or control inventory. OLAP databases are used by analysts and management to support long term decision making.


       
Online Transaction Processing (OLTP) databases support everyday business operations. The operations of an OLTP database include reading, writing and updating. These basic transactions are current and include data entry and changes made to entities such as orders, customers, inventory, etc. When designing an OLTP database we begin with an ER diagram that consists of Entities and Relationships. OLTP data is stored in relational tables.



              

Online Analytical Processing (OLAP) databases contain current and historical business data used to show changes in data over time. OLAP databases periodically update and have read only functions that are used for reporting. When designing an OLAP database we use Star Schema comprised of Facts and Dimensions. OLAP data is stored in multidimensional structures such as data cubes.




Ram, Sudha. (January 2014). MIS 587 – Business Intelligence: Data Warehouse Design Cycle. Lecture Conducted from University of Arizona, Tucson, AZ. Accessed from http://courses.eller.arizona.edu/mis/587/ram/Lecture3_v3/

Wednesday, February 5, 2014

Big Data Explosion





The rate at which we are generating data is truly truly outrageous. In 2012 90% of all data in the entire history of data had been created in the previous two years. Currently 2.7 Zetabytes of data exist today and it is predicted that by 2020 the amount of data will be 50 times that of today.

According to the McKinsey Global Institute, it is predicted that 1.8 billion people in developing economies will transition into the global consumer class and an estimated 2.5 billion to 3 billion additional people will potentially be connecting to the internet. As mobile computing devices become more affordable and readily available, it is becoming easier to connect with the world. This explosive rise in users and connectivity will likely drive the development of developing nations by providing huge business opportunities through data. In many cases internet access will be available before access to reliable electricity or water.

With the immense number of internet users networking, purchasing, banking, and socializing, we are in a world where connectedness is becoming extremely pervasive. All data has the potential to be tracked and this has created a gold mine for business analysts to discover trends. Business are able to offer extremely personalized and targeted services, and in some cases too extreme.



Andrew Pole is a masterful analyst. He developed a pregnancy-prediction model while working for Target. Using market basket analyst he was able to determine correlations between products and stages of pregnancy.

There is a case where advertisements for maternity clothing, nursery furniture and pictures of smiling infants were sent to a high school girl. Her father furiously thought that Target was trying to encourage her daughter to become pregnant. He later found out that she actually was pregnant and had not told anyone about it. Her shopping history matched up with trends such as purchasing large quantities of unscented lotion along with calcium, magnesium and zinc supplements. As a male, this makes me wonder if I would still receive the same advertisements from purchasing these types of items.

The response from the public towards predictive analysis marketing is generally negative. It is perceived as creepy and intrusive. Target has since planted non-pregnancy related ads next to their pregnancy ads to appear more random to their pregnant demographic.

“And we found out that as long as a pregnant woman thinks she hasn't been spied on, she’ll use the coupons. She just assumes that everyone else on her block got the same mail for diapers and cribs. As long as we don’t spook her, it works.”




OgilvyOne Worldwide. Big Data for smarter customer experiences. <http://adayinbigdata.com/>

Chui, Michael, James Manyika, Jacques Bughin, Brad Brown, Roger Roberts, Joi Danielson, and Shalabh Gupta. "The Next Three Billion Digital Citizens." Ten IT-enabled Business Trends for the Decade Ahead (2013

Duhigg, Charles. "How Companies Learn Your Secrets." The New York Times. 16 Feb. 2012. 5 Feb. 2014 <http://www.nytimes.com/2012/02/19/magazine/shopping-habits.html>.